Welcome

Welcome to EPsy 8251: Methods in Data Analysis for Educational Research I. This is the first course of a two-semester statistical methods sequence for doctoral students in education.


Instructor

Andrew Zieffler (zief0002@umn.edu)
Office: Education Sciences Building 178
Office Hours: Tuesday 9:00 AM–10:00 AM; and by appointment

Teaching Assistant

Mireya Smith (mart1799@umn.edu)
Office: Education Sciences Building 192
Office Hours: Thursdays 9:00 AM–11:00 AM; and by appointment


Classroom


Course Content and Syllabus

The statistical content for EPsy 8251 includes rigorous coverage of estimation and hypothesis testing with a particular focus on ANOVA and multiple linear regression.

  • The course syllabus is available here.


Textbooks

The primary course textbook is available via the University of Minnesota library.

The secondary course textbook (available via Amazon) is


Schedule

Below is the tenative schedule for the class. The dates are subject to change at the instructor’s discretion. Readings should be completed prior to class.


Calendar


T/R M/W Reading Topic Notes Script
  Sept. 03 Sept. 04 Welcome to EPsy 8251
Unit 01: Introduction to Statistical Computing
Sept. 05 Sept. 09 Introduction to R and RStudio
Sept. 10 Sept. 11 Data Wrangling with dplyr
Sept. 12 Sept. 16 Plotting with ggplot2
Unit 02: Introduction to Linear Regression
Sept. 17 Sept. 18 Simple Linear Regression: Description
[Notes and script file updated 09-24-2019]
Sept. 19 Sept. 23
Sept. 24 Sept. 25 Least Squares Estimation
[Notes and Script file updated 09-24-2019]
Sept. 26 Sept. 30
Sept. 26 Sept. 30 Correlation and Standardized Regression
Oct. 01 Oct. 02
Unit 04: Statistical Uncertainty and Inference
Oct. 03 Oct. 07 Coefficient-Level Inference
Oct. 08 Oct. 09
Oct. 10 Oct. 14 Model-Level Inference
Oct. 15 Oct. 26
Unit 04: Multiple Linear Regression and Statistical Control
Oct. 17 Oct. 21 Introduction to Multiple Linear Regression
Oct. 22 Oct. 23
Oct. 24 Oct. 28 Understanding Statistical Control
Oct. 29 Oct. 30
Unit 05: Model Assumptions
Oct. 31 Nov. 04 Assumptions of the Regression Model
Nov. 05 Nov. 06
Unit 06: Categorical Predictors
Nov. 07 Nov. 11 Dummy Coding Categorical Predictors
Nov. 12 Nov. 13
Nov. 14 Nov. 18 Effects Coding Categorical Predictors

Assignments

Below are the due dates for the assignments, as well as links to the RMD and PDF files for each assignment. The due dates may change at the instructor’s discretion. Any revised due dates will be announced in class and posted to the website.


Assignment Due Date (T/R) Due Date (M/W) PDF
Assignment #1: Introduction to Statistical Computing
[Updated 09-09-2019]
Sept. 19 Sept. 23
Assignment #2: Simple Regression: Description Oct. 01 Oct. 02
Assignment #3: Correlation and Standardized Regression Oct. 10 Oct. 14
Assignment #4: Simple Regression: Inference
[Updated 09-09-2019]
Oct. 22 Oct. 23
Assignment #5: Introduction to Multiple Regression Oct. 31 Nov. 04
Assignment #6: Regression Assumptions Nov. 12 Nov. 13

Data

Below are the links to the data sets and data codebooks used in the notes, scripts, and assignments.


Name Data Codebook
evaluations.csv
fertility.csv
goodreads.csv
keith-gpa.csv
mn-schools.csv
riverview.csv
state-education.csv
waffle-house.csv